Ultrafast X-ray tomography is a recently developed imaging technique for multiphase flows. As with conventional X-ray tomography it involves reconstruction of images from X-ray projection data. If used for multiphase flow measurements, it moreover needs to be complemented with automated image processing algorithms for the extraction of flow features, such as gas holdup profiles, bubble/particle size distributions or disperse phase velocities. So far, image reconstruction is carried out with the standard filtered back-projection technique, which is fast but may not be optimal in the presence of noisy or corrupted data. As the latter is a frequent issue, search for optimal image reconstruction and data processing algorithms is continuously ongoing. This paper serves as a foundation of the image reconstruction and processing framework for the application to multiphase flow. A description is given of the procedure from reconstruction to thresholding to property extraction of ultrafast X-ray tomographic images. Two reconstruction techniques, FBP and SART are employed on the basis of phantom measurements. Each technique is evaluated separately, for FBP regarding the choice of filter and for SART regarding the termination criteria. Image reconstruction resolution, computational costs and sensitivity to the threshold value are investigated. Based on the analysis, FBP with the Ram-Lak filter is selected for image processing purposes. Furthermore, it is shown that from experiments with moving objects, there is fair agreement between measurements and the phantom dimensions. The described imaging process can be applied to different attenuation materials, simulating gas-solid and gas-liquid properties. (C) 2018 Elsevier Ltd. All rights reserved.